Radar-Based Heart Rate Estimation Method Under Respiratory Harmonic Interference
Non-contact vital sign monitoring using millimeter-wave radar has emerged as a promising alternative to contact-based devices for continuous healthcare and elderly care applications. However, accurate heart rate estimation remains challenging because the weak cardiac-induced chest displacement is approximately an order of magnitude smaller than respiratory motion, and its fundamental frequency is frequently masked by higher-order respiratory harmonics. Here we propose a signal processing framework that addresses this challenge through three integrated stages: a slow-time phase correlation method that enhances the signal-to-noise ratio by coherently aggregating vital sign energy from adjacent range bins; an adaptive harmonic matching filtering approach based on complementary ensemble empirical mode decomposition that isolates and suppresses respiratory harmonic interference; and autocorrelation-based heart rate estimation. Experimental results obtained with a 77 GHz FMCW radar demonstrate that the proposed method achieves heart rate estimates within 5% error of reference wearable sensors in the presence of respiratory harmonics, with robustness confirmed through long-duration testing. This framework provides a practical solution for reliable radar-based heart rate monitoring without requiring subject-specific calibration or specialized hardware modifications.